Effect of Seeding Density and Seeding Methods on the Dry Matter Yield of Barnyard Millet

2021 ◽  
Vol 41 (3) ◽  
pp. 205-209
Author(s):  
Bae Hun Lee ◽  
Seung Hak Yang ◽  
Mirae Oh ◽  
Ki Choon Choi ◽  
Hyung Soo Park
Keyword(s):  
Dry Matter ◽  
Seeding Density ◽  
Dry Matter Yield ◽  
Barnyard Millet

scholarly journals Effects of seeding density, cutting height and month of harvest on the dry matter yield and protein content of Ubon Stylo

1969 ◽  
Vol 99 (2) ◽  
pp. 147-156
Author(s):  
Jorge Olivares ◽  
Elide Valencia ◽  
Rafael Ramos-Santana
Keyword(s):  
Dry Matter ◽  
The Other ◽  
Seeding Density ◽  
Second Phase ◽  
Dry Matter Yield ◽  
Seeding Rate ◽  
Four Levels ◽  
Time Of Year ◽  
High Yields ◽  
Cutting Height

Four levels of seed were used for establishment of Ubon Stylo (Stylosanthes guianensis var. vulgaris x var. pauciflora) in the first phase of this research, and in the present second phase, this same variable plus three cutting heights and four months of harvest at 90-d intervals were evaluated as to their effects on forage dry matter yield (DMY) and crude protein (CP) content. The seeding levels (5, 10, 15 and 20 kg/ha) constitute the main plots; cutting heights (10, 15 and 20 cm) formed the subplots; and months of harvest (March, June, September and December) the sub-subplots. Statistical analysis revealed that DMY was not significantly influenced by cutting height or by the interactions of this variable with each of the other two. Month of harvest did exert a significant effect (P<0.05) on DMY, and seeding density showed a similar tendency (P<0.063); also an interaction (P<0.05) between these two variables was detected. Mean DMY, expressed as annual equivalent (kg/ha), corresponding to the four consecutive harvests from March to December were: 5,949; 11,285; 8,105 and 6,543; with a general mean of 7,970. Values of DMY corresponding to the four progressive seeding rates from 5 to 20 kg/ha seed were: 7,488; 8,347; 8,375 and 7,672 kg/ha. The seeding rate x harvest interaction is illustrated by the fact that the highest DMY at the June harvest (13,975 kg/ha) was obtained with 15 kg/ha seed, whereas the maximum DMY at the other three harvests corresponded to the 10 kg/ha seeding rate. The general mean of the forage CP content was 13.4% and no significant effects were exerted by the three factors under study or their interactions. The present results confirm the earlier conclusion that 10 kg/ha is the optimum seeding rate for establishment of Ubon Stylo to promote a high DMY without incurring in unnecessary additional expense. Furthermore, the high yields obtained in the summer season suggest that the cutting interval could be shortened to improve the CP content at this time of year.

Season and date of harvest effects on dry matter yield of sunn hemp (Crotalaria júncea L.) 'Tropic Sun' in northwestern Puerto Rico.

1969 ◽  
Vol 95 (3-4) ◽  
pp. 179-191
Author(s):  
Ana Santos ◽  
Elide Valencia ◽  
Elvin Román-Paoli ◽  
Rafael Ramos-Santana
Keyword(s):  
Puerto Rico ◽  
Biomass Production ◽  
Dry Matter ◽  
Agricultural Research ◽  
Seeding Density ◽  
Research Station ◽  
Nitrogen Accumulation ◽  
Dry Matter Yield ◽  
Harvest Dates ◽  
Sunn Hemp

An experiment to evaluate the effects of planting season and harvest dates on biomass production and nitrogen accumulation by sunn hemp was conducted at the Agricultural Research Station, Isabela, Puerto Rico. Sunn hemp Tropic Sun' was established in an Oxisol soil (Cotito series) at a seeding density of 10 kg/ha. Dry matter yield (DMY) was estimated at 71,92 and 121 days after planting (DAP) in June and November. Effects of both major variables were significant (P > 0.05) for DMY, the June planting far surpassing that of November (15,831 vs. 5,665 kg/ha); DMY increased progressively for the three harvest dates (7,704; 11,141; and 13,398 kg/ha). Maximun biomass production (20,734 kg/ha) was obtained at 121 DAP in June, thus exceeding by threefold that of November at 121 DAP (6,062 kg/ha). Nitrogen accumulation followed a similar pattern, with that of June surpassing that of November (352 vs. 147 kg/ha) and values ascending for the successive harvest dates (193, 254, and 303 kg/ha). Differences (P < 0.05) in N concentration were found by comparing the upper plant canopy with the lower. Expressed as crude protein (CP) the maximum value corresponded to that of the upper canopy at 92 DAP in November (19.0%), whereas the corresponding lower canopy value was only 4.72%. Based on its high biomass production and N accumulation, this legume could provide multiple beneficial effects when included in short crop rotations of sustainable production systems, taking advantage of the most favorable season and harvest stage. The present results suggest that 'Tropic Sun' planted in summer has good potential as a cover crop and green manure.

scholarly journals Seeding system and density for winter Urochloa ruziziensis intercropped with sorghum between soybean crops

2018 ◽  
Vol 9 (3) ◽  
pp. 340-350 ◽  
Author(s):  
Marco Antônio Buffara ◽  
Alessandro Guerra da Silva ◽  
Itamar Rosa Teixeira ◽  
Kátia Aparecida de Pinho Costa ◽  
Gustavo André Simon ◽  
...  
Keyword(s):  
Grain Yield ◽  
Dry Matter ◽  
Seeding Density ◽  
Seed Density ◽  
Dry Matter Yield ◽  
Crop Season ◽  
Plant Coverage ◽  
Biomass Yields ◽  
Viable Seeds ◽  
Sorghum Grain

The intercrop of grain sorghum with Urochloa ruziziensis allows the production of grains and biomass in the winter. Thus, the objective of this study was to identify the more adequate seeding system and seed density for Urochloa ruziziensis intercropped with sorghum between soybean crops to obtain high grain and biomass yields with these species and evaluate the performance of the subsequent soybean crop. The experiments were carried out in the winter of 2015 and in the 2015-2016 crop season in Rio Verde GO, and Santa Helena de Goiás GO, Brazil. The treatments consisted of three seeding systems (in-row, inter-row, and broadcast), and five seed densities (2, 4, 6, 8, and 10 viable seeds m-2) of U. ruziziensis intercropped with sorghum, using monocultures of sorghum and U. ruziziensis as controls. The seeding density of 8 viable seeds m-2 of U. ruziziensis using in-row seeding, and up to 10 viable seeds m-2 using inter-row, and broadcast seedings do not decrease sorghum grain yield. Increasing seeding density of U. ruziziensis increases its dry matter yield, and the total dry matter yield when intercropped with sorghum. The intercrop of sorghum with U. ruziziensis increases the soil plant coverage. The dry matter of the intercrop of sorghum with U. ruziziensis does not affect soybean grain yield.

Optimum harvest date of maize for biogas and silage purposes

2009 ◽  
Vol 57 (2) ◽  
pp. 119-125
Author(s):  
G. Hadi
Keyword(s):  
Dry Matter ◽  
Biogas Production ◽  
Weather Conditions ◽  
Vegetation Period ◽  
Dry Mass ◽  
Matter Content ◽  
Harvest Date ◽  
Dry Matter Content ◽  
Dry Matter Yield ◽  
Vegetative Organs

The dry matter and moisture contents of the aboveground vegetative organs and kernels of four maize hybrids were studied in Martonvásár at five harvest dates, with four replications per hybrid. The dry matter yield per hectare of the kernels and other plant organs were investigated in order to obtain data on the optimum date of harvest for the purposes of biogas and silage production.It was found that the dry mass of the aboveground vegetative organs, both individually and in total, did not increase after silking. During the last third of the ripening period, however, a significant reduction in the dry matter content was sometimes observed as a function of the length of the vegetation period. The data suggest that, with the exception of extreme weather conditions or an extremely long vegetation period, the maximum dry matter yield could be expected to range from 22–42%, depending on the vegetation period of the variety. The harvest date should be chosen to give a kernel moisture content of above 35% for biogas production and below 35% for silage production. In this phenophase most varieties mature when the stalks are still green, so it is unlikely that transport costs can be reduced by waiting for the vegetative mass to dry.

Nitrogen Fertilization of Basil

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 481a-481 ◽  
Author(s):  
M. Rangappa ◽  
H.L. Bhardwaj
Keyword(s):  
Moisture Content ◽  
Dry Matter ◽  
Calcium Nitrate ◽  
Control Treatment ◽  
Dry Matter Yield ◽  
Sweet Basil ◽  
Broad Leaf ◽  
Yield Difference ◽  
Optimum N Rate ◽  
N Rates

Sweet basil (Ocimum basilicum) is an important culinary herb in Virginia and other areas. The objective of this study, conducted during 1997, was to determine optimal N rate for fresh and dry matter yield. Seed of Broad Leaf sweet basil were direct-seeded on 18 June in rows 0.75 m apart in a RCBD design with 8 replications. Four N rates (0, 25, 50, and 75 kg N/ha) were used. Calcium nitrate (15.5% N) was used as the fertilizer source. All plants from 1-m row length from middle row of each plot were harvested by hand on 23 Sept. and fresh weights were recorded. The plant material was dried at 70°C for 48 h to record dry weights. The moisture content at harvest was calculated from fresh and dry weights. The fresh yields following 0, 25, 50, and 75 kg N/ha were 3.7, 5.4, 6.4, and 6.8 kg/m2, respectively. The yield difference between two highest N rates was not significant, however, both these rates had significantly higher yield than the two lowest rates. Similar results were also obtained for dry matter yields. The highest N rate of 75 kg N/ha resulted in significantly higher dry matter yield (1.3 kg/m2) as compared to the other three rates. The lowest dry matter yield was obtained after the control treatment (0.6 kg/m2). An opposite relationship between N rate and moisture content was observed when the highest moisture content resulted from control and 50 kg N/ha treatments. These results indicate that optimum N rate for sweet basil in Virginia is 50 to 75 kg/ha.

Diurnal Variation in Alfalfa ( Medicago sativa L.) Dry Matter Yield and Overnight Losses in Harvested Alfalfa Forage 1

1973 ◽  
Vol 65 (3) ◽  
pp. 413-417 ◽  
Author(s):  
W. R. Knapp ◽  
D. A. Holt ◽  
V. L. Lechtenberg ◽  
L. R. Vough
Keyword(s):  
Diurnal Variation ◽  
Medicago Sativa ◽  
Dry Matter ◽  
Dry Matter Yield ◽  
Medicago Sativa L

Effects of Seeding Rate on the Dry Matter Yield and Nutritive Value of Fall‐Grown Oat

cftm ◽  
2016 ◽  
Vol 2 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Wayne K. Coblentz ◽  
Jason S. Cavadini
Keyword(s):  
Dry Matter ◽  
Nutritive Value ◽  
Dry Matter Yield ◽  
Seeding Rate

Water‐phosphorus coupling enhances fine root turnover and dry matter yield of alfalfa under drip irrigation

2021 ◽  
Author(s):  
Xuanshuai Liu ◽  
Junwei Zhao ◽  
Junying Liu ◽  
Weihua Lu ◽  
Chunhui Ma ◽  
...  
Keyword(s):  
Drip Irrigation ◽  
Dry Matter ◽  
Fine Root ◽  
Root Turnover ◽  
Dry Matter Yield ◽  
Fine Root Turnover

scholarly journals Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3971
Author(s):  
Gabriel Silva de Oliveira ◽  
José Marcato Junior ◽  
Caio Polidoro ◽  
Lucas Prado Osco ◽  
Henrique Siqueira ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Dry Matter ◽  
Pearson Correlation ◽  
Genetic Correlations ◽  
Remote Sensing Data ◽  
Breeding Program ◽  
Yield Traits ◽  
Dry Matter Yield ◽  
Breeding Programs ◽  
Ground Truth Data

Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) and computer vision are crucial to increase the efficiency of forage breeding programs, to support high-throughput phenotyping (HTP), aiming to estimate parameters correlated to important traits. The main goal of this study was to propose a convolutional neural network (CNN) approach using UAV-RGB imagery to estimate dry matter yield traits in a guineagrass breeding program. For this, an experiment composed of 330 plots of full-sib families and checks conducted at Embrapa Beef Cattle, Brazil, was used. The image dataset was composed of images obtained with an RGB sensor embedded in a Phantom 4 PRO. The traits leaf dry matter yield (LDMY) and total dry matter yield (TDMY) were obtained by conventional agronomic methodology and considered as the ground-truth data. Different CNN architectures were analyzed, such as AlexNet, ResNeXt50, DarkNet53, and two networks proposed recently for related tasks named MaCNN and LF-CNN. Pretrained AlexNet and ResNeXt50 architectures were also studied. Ten-fold cross-validation was used for training and testing the model. Estimates of DMY traits by each CNN architecture were considered as new HTP traits to compare with real traits. Pearson correlation coefficient r between real and HTP traits ranged from 0.62 to 0.79 for LDMY and from 0.60 to 0.76 for TDMY; root square mean error (RSME) ranged from 286.24 to 366.93 kg·ha−1 for LDMY and from 413.07 to 506.56 kg·ha−1 for TDMY. All the CNNs generated heritable HTP traits, except LF-CNN for LDMY and AlexNet for TDMY. Genetic correlations between real and HTP traits were high but varied according to the CNN architecture. HTP trait from ResNeXt50 pretrained achieved the best results for indirect selection regardless of the dry matter trait. This demonstrates that CNNs with remote sensing data are highly promising for HTP for dry matter yield traits in forage breeding programs.

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